Mobile crowdsensing systems are designed to take advantage of ubiquitous mobile devices for sensing and collecting data from physical environments to implement data analytic tasks. Traditionally, centralized AI/ML architectures are often used to realize intelligent mobile crowdsensing [1]}, but they require direct access to sensing data which raises privacy concerns. Moreover, the utilization of a single server to handle all sensed data is not efficient especially when data are often distributed across a large-scale network. FLchain not only enables highly scalable intelligent edge data crowdsensing solutions but also provides high degrees of privacy and security based on FL and blockchain integration. For example, an FLchain scheme is studied in [2]} to construct a mobile crowdsensing system based on Unmanned Aerial Vehicles (UAVs), as indicated in Fig. REF . Blockchain is employed to build a decentralized learning network by interconnecting UAVs with data task publishers through an immutable ledger, which ensures that data training and model exchange among UAVs are monitored and traced for attack detection and data modification prevention.
